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@6a4fbf2
by Dean Petersdeanpeters/product-manager-skills7.1k stars
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Structure a spoken PM product-sense answer with assumptions, segmentation, pain-point prioritization, and MVP tradeoffs. Use when practicing design, improve, or build-next interview questions.

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Use this Skill: https://skilld.dev/gh/deanpeters/product-manager-skills/product-sense-interview-answer

This session only. Nothing lands on disk.

examplesimprove-youtube.md

≈976 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Example: Improve YouTube

Prompt: "How would you improve YouTube?"

Why this is a strong example

This example works because it does not treat "YouTube" as one giant undifferentiated product. It narrows the target user, picks one pain point, and earns the final MVP choice through explicit tradeoffs.

Condensed Walkthrough

1. Clarify

  • Scope the product to the core YouTube viewing experience rather than Shorts, Music, or TV.
  • Clarify whether the focus is viewers, creators, or advertisers.
  • If the interviewer does not answer, assume the full ecosystem is in scope but commit to prioritizing one player.

2. Rationale

  • Online video is a massive attention market with intense competition.
  • The deeper issue is not just watch time; it is whether users feel their time was well spent.
  • YouTube's unique advantage is the breadth of creator supply across learning, entertainment, and niche content.
  • Thesis: recommendation quality is optimized for engagement more than intentional satisfaction.

3. Product Goal

Help viewers consistently find content they are glad they watched, so that YouTube becomes a platform people choose intentionally rather than habitually.

4. Segmentation

Ecosystem players:

  • Viewers
  • Creators
  • Advertisers
  • Talent managers / networks
  • Moderation and trust teams

Chosen player: viewers

Primary dimension: viewing intent

  • Goal-directed learning
  • Entertainment browsing
  • Deep-dive research

Chosen segment: goal-directed learners

Secondary dimension: expertise level

  • Beginners
  • Intermediate
  • Advanced

Chosen segment: beginners

Persona: Priya is a 28-year-old marketing coordinator using YouTube to learn practical work skills quickly. She cares about finding trustworthy, well-structured content without wasting time in low-signal recommendation loops.

5. Pain Points

Journey stages:

  • Search
  • Selection
  • In-session learning
  • Follow-through

Key pain points:

  • No clear starting point for a topic
  • Quality is hard to judge before clicking
  • Too many similar-looking tutorials
  • Old content outranks better current content
  • Recommendations pull the user off task
  • No structured progression from one concept to the next
  • No record of learning progress

Top pain point: no structured progression

  • Frequency: shows up in almost every learning session after the first video
  • Severity: blocks the job to be done because skill-building requires sequence, not random adjacent content

6. Solution

Option 1: Learning Paths that sequence the best beginner videos into a guided curriculum.

Option 2: Intent-Aware Recommendations that hold the session to the user's stated learning goal.

Option 3: Key Moments Index that lets users jump directly to the concept they need inside each video.

Comparison:

  • Learning Paths: High user impact - directly solves progression. High effort - ranking, sequencing, and new UI.
  • Intent-Aware Recommendations: Medium user impact - reduces distraction. Medium effort - recommendation-system changes.
  • Key Moments Index: Medium user impact - improves efficiency inside videos. Medium effort - transcript and chapter labeling work.

MVP winner: Learning Paths

Core features:

  • Topic-based path of 5-8 sequenced videos
  • Progress tracking across sessions
  • "Continue learning" re-entry point

v1 exclusions:

  • No quizzes
  • No creator-submitted path editing

Closing line:

"I'd focus on beginner goal-directed learners, specifically around the pain of no structured progression, and build Learning Paths as the first bet."

What to notice

  • The goal is an outcome, not a feature
  • The segment is narrow enough to matter
  • The pain point is a user friction, not a missing capability
  • The final MVP is chosen after comparison, not announced from intuition alone

Source: SKILL.md on GitHub

Third-party checks

No alerts17d4 checks · Risk SAFE
  • Gen Agent Trust Hub17d

    The skill is a text-based coaching framework designed to help users prepare for product management interviews. It provides a structural spine and templates for organizing spoken answers. Analysis confirms no malicious code, network calls, or security vulnerabilities are present.

  • Socket17d

    No alerts

  • Snyk17d

    Risk: LOW · No issues

  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

Provenance

Signed by skilld at 6a4fbf2. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last month.

Activeupdated 3 months ago

Capability

argument-hint
[interview prompt]
type
component
theme
career-leadership
Other metadata
intent
Coach PM candidates through open-ended product-sense interviews using a repeatable six-part answer spine: clarify, rationale, goal, segmentation, pain points, and solution choice. Use this to practice product design and product improvement questions, avoid solution-first answers, and produce responses that sound thoughtful out loud rather than over-scripted on the page.
best_for
[
  "Practicing product design and product improvement interview questions",
  "Coaching candidates who jump to solutions too quickly",
  "Turning messy ideation into a crisp spoken interview answer"
]
scenarios
[
  "How would you improve YouTube?",
  "Design a product for travelers with flight anxiety",
  "What would you build next for DoorDash?"
]
estimated_time
20-30 min

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